Development and exploitation of a controlled vocabulary in support of climate modelling

There are three key components for developing a metadata system: a container structure laying out the key semantic issues of interest and their relationships; an extensible controlled vocabulary providing possible content; and tools to create and manipulate that content. While metadata systems must allow users to enter their own information, the use of a controlled vocabulary both imposes consistency of definition and ensures comparability of the objects described. Here we describe the controlled vocabulary (CV) and metadata creation tool built by the METAFOR project for use in the context of describing the climate models, simulations and experiments of the fifth Coupled Model Intercomparison Project (CMIP5). The CV and resulting tool chain introduced here is designed for extensibility and reuse and should find applicability in many more projects.

Rapid word learning by 15-month-olds under tightly-controlled conditions

Infants (12 to 17 months) were taught 2 novel words for 2 images of novel objects, by pairing isolated auditory labels with to-be-associated images. Comprehension was tested using a preferential looking task in which the infant was presented with both images together with an isolated auditory label. The auditory label usually, but not always, matched one of the images. Infants looked preferentially at images that matched the auditory stimulus. The experiment controlled within-subjects for both side bias and preference for previously named items. Infants showed learning after 12 presentations of the new words. Evidence is presented that, in certain circumstances, the duration of longest look at a target may be a more robust measure of target preference than overall looking time. The experiment provides support for previous demonstrations of rapid word learning by pre-vocabulary spurt children, and offers some methodological improvements to the preferential looking task.